Speaker 1 00:00:08 Welcome to the breakout growth podcast, where Sean Ellis and Ethan Gar interview leaders from the world's fastest growing companies to get to the heart of what's really driving their growth. And now here are your hosts, Sean Ellis and Ethan Gar
Speaker 2 00:00:26 In this week's episode of the breakout growth podcast, Ethan Gar and I chat with my coauthor of hacking growth, Morgan brown. I am so excited to finally get Morgan on the podcast. So we could geek out about all our new growth learnings. Since we wrote the book, since that time, he has had growth roles at Facebook and now Shopify, where he's VP of growth. These companies are an order of magnitude larger than anything we'd done prior to the book. So Ethan, what stood out at you from this conversation?
Speaker 3 00:00:55 Mostly it was Morgan's background. I mean, literally as we were chatting, he has this great neon sign in the background and a formula, one race track map. I mean, his background is mesmerizing, but joking aside for me, this was such a cool opportunity. I mean, who else gets to sit down in a riff session between the two guys who literally wrote the book on growth and then prod them on how they would rethink that book with the benefit of 2020 hindsight, having built a growth approach using this book as a guide, I can tell you this just felt really valuable.
Speaker 2 00:01:24 Yeah. It was super fun exploring growth with both of you guys. Um, and then even tying it back to our discussion that we had with Karen Flanagan from HubSpot a few weeks ago. Yeah. That's, that's another company that's working at an enormous scale and Kieran's take was that at that size, you really could only focus on big bets because small optimizations just don't move the needle. Morgan was kind of saying the opposite. So it's, it's interesting. There's not an exact playbook here and, and everybody has different things they want to emphasize. And so for Morgan, he was really emphasizing the iterative approach that we highlight in the book.
Speaker 3 00:02:01 Yeah. It's neat to see, you know, agreement and disagreement between our guests, but as you mentioned in the conversation, Sean, they may not really be that far apart on this one, since Karen was probably talking more about top of funnel marketing and Morgan was talking more generally about product growth initiatives, but it's still, it's just so interesting to think about how massive scale really impacts decision-making
Speaker 2 00:02:20 Right. And the other thing to keep in mind is that Facebook is probably the most sophisticated growth organization on the planet. And Morgan talks about the focus that they have for understand, identify and execute as a guiding principle. And, you know, just that intentionality of just really digging into the root of the problem you're trying to solve is fundamental to growth, whether you're a 10 person organization or a 10,000 person organization. So the book, the book obviously addresses it, but I think that was one of the areas where Morgan and I both agreed. We'd probably put a lot more emphasis on really understanding the, if we rewrote it today. Yeah.
Speaker 3 00:03:01 Okay. So now are you going to write a second edition?
Speaker 2 00:03:05 It's not in the books, so to speak.
Speaker 3 00:03:08 Yeah, well let's get into it.
Speaker 2 00:03:11 Yeah. So, um, absolutely. But you know, before we get started with it, I want to talk about hyper-growth at scale. That's something that our listeners really would benefit if they checked out this week, sponsor rise with SAP S four HANA cloud hyper-growth companies get up and running quickly with this low cost, easy to implement cloud ERP solution. So if you're working to power, breakout growth, success in your business, please check out sap.com/high growth.
Speaker 3 00:03:40 Yeah. And just before we jump in, if you're finding value in the breakout growth podcast, please take a moment to leave a rating and review and subscribe wherever you listen. It really helps us spread the word. So until we jump in with Morgan,
Speaker 2 00:03:52 All right, let's do it. Hey Morgan. Welcome to the breakout growth podcast. Hey
Speaker 4 00:04:05 Sean. Thanks for having me. Hey Nathan.
Speaker 3 00:04:07 Hey, nice to see you.
Speaker 2 00:04:09 Yeah, we are. We are so excited to have you on it's a, I'm surprised you weren't the very first guest that we invited onto the podcast. Now I'm super
Speaker 4 00:04:17 Excited to be here. Thanks for having me.
Speaker 2 00:04:19 Yeah, definitely. We got to work the kinks out with the podcast before, uh, before bringing in the best of the guests. So
Speaker 3 00:04:27 What are you saying, Sean? I was your first step. Well, I was not the first guest, but I was actually your first recording. So it kind of hurts my,
Speaker 2 00:04:32 Definitely a work, the kinks out guy,
Speaker 3 00:04:37 My feelings are hurt, but we'll have some fun today.
Speaker 2 00:04:41 Right. So, um, you know, I really want to keep us focused today, um, on yeah, for anyone who, who doesn't know Morgan and I wrote a book together hacking growth. And so I really want to keep today focused on, uh, the theme around what have you learned since hacking growth, Morgan, Scott, uh, incredible experience. Since we put the book out, he spent time on the Facebook team and now he's on the Shopify team. So he's really driving growth at a scale that, um, neither of us had come close to driving growth that prior to writing the book. So I think that's a great place to start with the questions of, you know, what, what is it like to be driving growth at that scale? And, and is, is the book applicable at that scale and sort of what, what are some of the key learnings that you may have gotten driving growth at that scale that almost, uh, either warrant a new book or, uh, you wish you had in the original book?
Speaker 4 00:05:36 Yeah, absolutely. Um, it has been kind of a wild ride. I think we wrote the book, I started writing it in 2015. It was published in 2017 since then I had the chance to work at Facebook now at Shopify. So yeah, really kind of, um, you know, particularly at Facebook getting into frankly, the canonical growth team growth company that has defined growth for the last decade. So it was pretty exciting for me. And it was actually pretty humbling when I joined the team. Uh, some folks had read the book and they're like, yeah, we do, we do this stuff. And I'm like, I know, but no one else does this stuff, which is why, which is why we wrote the book. Um, but, uh, but no, it was a really, I think some of the things that I've learned, um, first of all, it just that scale matters, um, scale is, uh, is a big input into how you think about the growth, uh, process, um, and, and how you prioritize and the things that you work on, you know, um, uh, at, at Facebook you're dealing with billions of people a month, uh, and any change that you make, uh, no matter how small it was going to affect tens of millions, if not hundreds of millions of people.
Speaker 4 00:06:47 Um, and so there is kind of a, you know, there's, there's both like upsides and downsides to that, right? So on the upside, you can run a ton of experiments. Like the number of experiments, uh, Facebook was running is, is pretty mind blowing. Um, when I left the company was running about 22,000 concurrent experiments at any given time. Wow. Which is just like hard to even wrap your wrap, your head around. And so the, the infrastructure that exists at the company to run experiments, to allow people to be in multiple experiments, um, the amount of data that you have available to you about the different types of changes you make and whether they work or not, uh, is core to just how you do things. Um, they have a internal tool called deltoid, which is a, an experimentation measurement tool. They have several other tools in the stack, but deltoid is kind of the big one.
Speaker 4 00:07:43 And if you make a change, it can tell you any metric what it did to it up down otherwise. And so you actually come to rely a lot on experimentation as validation for your ideas is just kind of core to everything, everything you do, which I don't think is necessarily true early on, like in an early stage company, uh, you know, like when we were running experiments that quality, we were growth hackers, you just don't have the data, right? Like you're, you're kind of, uh, you kind of like putting things out there, you have a good hypothesis for it. You're going to kind of wait and see what happens, but it's just kind of a different level of, uh, of sophistication. I think the other thing too, is that because you have such a large population at these companies, these big tech companies, every surface, uh, every area is ripe for optimization and experimentation.
Speaker 4 00:08:32 It's a ripe for growth. So if you think about the number of funnels that exist in a product like Facebook or Shopify or Amazon, it's actually extraordinary. How many of these sequences actually exist? You know, we tend to think of funnels as like, Hey, a signup funnel or an onboarding funnel, but like you can think of a funnel as, you know, changing your profile picture. Um, you know, you can think of a, uh, funnel as, um, you know, adding a photo to a post or posting an Instagram story. And when you get to that level of detail, there's tons of opportunities to do exactly what we talked about in the book. That was one of the things that was exciting for me is like, no, this stuff really matters. Like remove friction, increase desire. Um, you know, all of that have a hypothesis, you know, really understand the root problems. Um, move quickly through a set of experimentation hypotheses, all really, still a whole that, that scale, but they just, you can go, you know, it exists everywhere. So it's kind of almost a limitless opportunity to constantly be, uh, fine tuning and improving things, which is, which is pretty extraordinary.
Speaker 3 00:09:45 Yeah. Can I just ask one question, you mentioned, you know, 22,000 concurrent experiments at Facebook, um, you know, Sean and I have worked with teams much smaller than, than Facebook's and we found, you know, often you'll run into places where one experiment will actually interfere with another experiment. Is there anything it built in at Facebook or anything at Shopify that helps manage that, that, so that you avoid, you know, one experiment damaging another experiment? I mean, it just seemed at that scale, like you could just stomp on things accidentally without even knowing that it's.
Speaker 4 00:10:19 Yeah, absolutely. So I think one of the, the abilities that Facebook has is, is kind of the multi assignment capability. So basically they've worked out the math where any given user can be in numerous experiments, uh, at one time and they can tease out the statistical validity of any given intervention. Um, so like I mentioned, there's kind of a stack of tools that exist. So deltoid is just like the reporting layer. There's other tools called like quick experiment and, um, others that basically allow you to, you know, kind of do the audience assignment in a way that lets all other interventions, all other experiments be equal for that group of people. But then the one that you're measuring is able to be teased out. So yeah, I think audience assignment, experiment, conflict, those are all challenges you start to run into at a larger scale, um, that companies, uh, you know, have to work through and that's, you know, frankly, something we're solving at, uh, Shopify right now is we've been really able to ramp the experimentation process about 10 X over the last year. And now we're hitting some of those local Maxima in terms of experiment, conflict, experimentation, layers, multi experiment, assignment, um, that we now are building for.
Speaker 2 00:11:33 So you, so you actually have massive teams at both of these companies as you're, as you're doing all of this as well. Um, are there, are there like specific roles for like experiment purity or, you know, being able to, uh, being able to vet those things you're talking about or is it more tool-based?
Speaker 4 00:11:51 Um, so, uh, it's a bit of a bit of both. So, um, on the tool side, obviously all of the, um, kind of the statistical analysis power is all done by data scientists or tools that leverage data science. So, um, you know, like math that's way over my pay grade. Um, uh, but I just, you know, know that it works. Um, and so, yeah, so like data science is a huge part of it, statistical modeling, uh, another huge part of it, but most of it at Facebook was abstracted into tools, um, that you could then use. But, um, you know, at Shopify, the tools are a bit, you know, Shopify is, uh, almost an order of magnitude smaller than Facebook in terms of team size. So, um, the tools are, are kind of newer or earlier in their journey. And so we do use like process and tooling to do that. So yeah, we have an experimentation and analysis team. Their goal is really to help any team at Shopify run trustworthy experiments. That's really our metric. It's not the number of experiments, but it's the number of trustworthy experiments. And that really talks to the need for a strong hypothesis, strong, um, understanding of the metrics and counter metrics you're trying to move and experiments set up and design and all of that type of thing. Um, and then also the, also the tooling. So yeah, there's kind of multiple teams and ways to go, go at it.
Speaker 2 00:13:14 Yeah. Maybe taking a little step backwards. I think most of the world is familiar with Facebook at this point. Um, but, uh, you know, Shopify has just kind of exploded on the scene in the last few years. And if you're not a small business, you may not actually, you know, you probably interact with Shopify all the time, but you may not realize it. Um, so can you give us a quick introduction to what actually Shopify is? Yeah,
Speaker 4 00:13:37 For sure. Shopify is a platform for commerce. Uh, it's a SAS based software model that lets anyone sell anything anywhere in the world. Um, it's really well-known for its online store. Uh, so you can sell a, you set up an e-commerce store very quickly, uh, but it also has retail point of sale. It also has Shopify payments that Shopify capital Shopify balance it's really designed to be the retail operating system for any, uh, any, any business that wants to sell, um, physical goods basically. So, uh, yeah, so that's, that's what we do at the growth team at Shopify, since there are so many different parts of the, of the business, the growth team at Shopify is responsible for the self-serve business effectively, which is anyone, any of us on this call could jump on to shopify.com, set up an online store, get a free trial and start selling. And that's really what the self-serve business businesses, uh, the growth team is responsible for is the number of people, uh, that power their online stores with Shopify.
Speaker 2 00:14:42 Yeah. So one of the things that kind of interesting for me is that I think of Shopify as almost like a counterbalance to Amazon where, you know, everyone talks about kind of Amazon squeezing out the mom and pops, and then you guys are really powering the, the mom and pops in a lot of way. I'm sure that that I'm like oversimplifying it there, but really interestingly in the last, uh, in the last few days, I did an order online where I paid for the order through a smaller store, but through Amazon payments. And then I track the order through an app called shop that then suddenly aggregated all of my orders and tracking the shipping for all of those orders, including everything I've ever ordered from Amazon. And then shop is actually a Shopify app, I believe. And so it's kind of just the blurring of it. It's not necessarily one against the other. It's like you guys must have a lot of, uh, overlap where, where there's, there's a lot of mutually beneficial relationship there as well with Amazon.
Speaker 4 00:15:44 Yeah. I think the, um, you know, obviously, uh, Amazon has aggregated so many, so much intent for shopping that it's an essential channel for a lot of a lot of businesses. Um, but they also wish that they own the customer experience. They had the customer data, they had, you know, the ability to interact directly with them. And so, um, you know, uh, big marketplaces, whether it's Amazon or Etsy or eBay effectively charge you rent to access, uh, you know, the aggregated customer demand, whereas Shopify basically allows you to own that end to end, um, relationship. And the reality is for a lot of merchants, they need both, um, they need marketplaces to generate kind of, you know, initial awareness and, and initial trial. And then, you know, they hope that they can convert people, you know, direct through their own online store because the unit economics are much better. The relationship's much better, you know? Um,
Speaker 2 00:16:40 They can retain long term buyers. Yeah, exactly.
Speaker 4 00:16:43 That's right. That's right. Lifetime value, you know, all that good stuff. So, uh, so yeah. Um, but yeah, I think like our, like Toby Lukey likes to say we arm the rebels and, uh, you know, I think Ben Thompson's written about the anti Amazon Alliance and stuff like that. So yeah, there's a lot of interesting commentary out there about it.
Speaker 3 00:17:01 Um, I'm sure we'll end up circling back through that as we talk more about the growth role and the self-serve business, but I wanted to just go back a little bit, you know, we talked about how, you know, you're working at such a large scale and what's interesting, I think about you is you've worked in businesses at both small and large scale when it comes to the Tesla and approach it. Both of you really laid out in the, in the book, what have you found really doesn't scale? Well from small organizations to large large organizations, if anything.
Speaker 4 00:17:31 Yeah. Um, so I think there's a bunch of things. I think one of the interesting things, um, when you get at really large scale, like particularly Facebook, a lot of the low-hanging fruit, easy stuff has been tried, uh, or optimized for. Right. And so you're basically, um, you're the, the level of fidelity of your hypothesis has to be much tighter and stronger and more specific than it is in early stage. Right? So for example, early stage, you might say like, Hey, you know, our landing page, um, uh, you know, isn't, you know, isn't converting at the rate that we want to, we think the reason is is that, um, people don't get the, you know, the value proposition or the headlines week or whatever. And we're going to go test a bunch of headlines when you get to like the Facebook scale. You're like, oh, actually like billions of people have seen that headline and it's been tested 18,000 different ways.
Speaker 4 00:18:30 It's going to be really hard to find a winner there. And so you really have to get very prescriptive around like what the actual problem is. You're trying to solve like that the five why's questioning model is, is really powerful here. That's probably something I wish we went to more on in the buckets, like actually getting down to the root cause of the problem versus just like, what is the observable problems? So for example, my landing page, isn't converting, Y you know, oh then, oh, these types of users sign up at a lower rate than these other types of users, whether it's like, because of a locale or a demographic or a device type that they're using, or that type of thing. Why do these people with this device type or this, uh, profile sign up at a lower rate? Oh, it's because, you know, they actually have more errors in their first name, field, or in the password field.
Speaker 4 00:19:23 Okay. Why do they have more errors in the password field? Oh, now there there's, they default to setting passwords that are typically too short for our password validation engine. Okay. Now my hypothesis is if I can make people set the appropriate length passwords, or if I can change the required password length by conversion rate for this audience will go up and therefore my conversion rate for the page will go up. And it's kind of that level of specificity that is like, if you start really broad and you bring that kind of broad, like surface level experimentation idea to like some of these larger scaled services, you'll find that most of that stuff has been tested or like, it's not, you don't actually understand the problem, uh, under that's causing the lower conversion rates or whatever. And so you're solving for the wrong thing. Um, and so I think that's, uh, that level of fidelity is really important. Uh, and kind of you lose that, uh, that kind of breaks down as you scale up.
Speaker 3 00:20:18 It's interesting because we just recently spoke with Kieran Flanagan from HubSpot. And, uh, he was saying, you know, at HubSpot scale and they're $37 billion company or something, he said, you know, we really can't afford to do small experiments at like, everything has to like anything. That's not a big bet just isn't worth worth it because it doesn't move the needle. But I imagine for you and Shopify, like where it's so nuanced, uh, small experiments can still have impacts you just, like you said, it's about finding the right hypothesis and really thinking about which hypotheses are going to move the needle. Is that more fair assessment for the business?
Speaker 4 00:20:59 Yeah. Yeah. So, um, I think Karen's super smart. Uh, so obviously he understands how it works for his business, but I would like very much disagree with kind of that point of view on the scale and optimization opportunities. Because I actually think, you know, at Facebook, some of the biggest mistakes that we saw being made in different like product teams and even within our own product team is where you have a big bet and the big bet is meant to solve a problem, but you don't actually really understand, like I said, the underlying causes of the problem. And so you're investing in a very risky, expensive enterprise, right? Like code and designs, like the most expensive way to learn, uh, out there. And so if all you're doing is these really big bets that take a lot of time to develop, um, a lot of engineering and design costs, but ultimately aren't really built on the foundation of like truly understanding of the problem you're trying to solve.
Speaker 4 00:21:56 You've like one burnt like that that's gonna fail. Um, and, and by, by definition, most bets are speculative. That's why they're called bets. Um, and, and two you've given up this huge opportunity costs to go kind of optimize, uh, what works. And so I did a poll on this on LinkedIn a while ago. Like what percentage of your product roadmap should be spent on big bets versus optimizations? And most of the Facebook PMs said, you know, 25% or less focused on big bets, 75% are more focused on optimization. And I think, you know, it depends, like you said, it depends on the stage your company's at just like your investment. You know, if you're young, you should invest in aggressive growth in your retirement portfolio. If you're old, like Sean, you should go to fixed income. Um, and so, uh, so that's, you know, or old like me. Um, so that's, uh, that's kind of, you know, I think you have an investment portfolio that you need to kind of think about, but I think actually being too overweight on big bets is, um, is typically like, uh, a problem, um, because they, they just have a lower hit rate. Um, and you kind of give up a lot of opportunity to, uh, actually like keep, you know, adding to your compounding interest over time. Um,
Speaker 2 00:23:18 The big bets applies most on top of funnel stuff that, um, you know, if you, if you're like mid funnel, lower funnel and you do a small optimization when you have massive numbers, that can make a huge impact. But if you're, if you're trying to figure out a new channel, you know, figuring out something, that's gonna send a hundred new people a day, it's just not going to make a difference for, for big scale businesses. I think the further down the funnel you go that, that sometimes the smaller optimizations can make a bigger impact.
Speaker 4 00:23:48 Yeah. I mean, like, so take a example at, at Shopify. Um, we, uh, we, we rely on several key channels, you know, paid acquisition, organic search of merchant referral. Um, but in order to like keep growing, we want to unlock new channels. So, you know, uh, this year we made a big bet on, on YouTube. We started with a small test and at the end of 2020, we've subsequently scaled it up over the course of 2021. So, you know, we spent a few million dollars in 20, 2010s of million dollars in, in 2021 and we'll spend, you know, maybe close to a hundred million dollars on it next year. And so, um, yeah, so there is certainly a place for them. I think, uh, there is just a marketing teams, product teams, they all want to build something new. Right. Um, and, uh, so kind of fighting against that urge of, you know, shipping something and forgetting it is, uh, is kind of the thing that I try to solve against. Like I tell my team all the time shipping is a milestone, not an end point, right? Yeah. You got the thing out there, but then, you know, we're a team we don't take just one shot on goal. We keep refining and refining and refining. So that's kind of the, the hedge
Speaker 2 00:25:02 That makes sense. And actually going backwards a little bit to where you talked about the five why's when I, when I think about some of my own learning since the book, um, I think my favorite quote that I've come across since, since the book is the Charles Kettering quote that says, uh, a problem well stated is half solved. I just think, um, I just think, you know, we, we want to run winning experiments, but we don't spend enough time to really understand the situation. As you're saying, if you can just keep digging down, peeling back the onion, get to the root issue. You may not need to brute force experiments at something to drive a result. You, when you actually understand what it is you're trying to fix you, you there's a good chance you're going to get a highly impactful winning experiment.
Speaker 4 00:25:47 Yeah. I couldn't agree more at Facebook. There was a framework that we use called understand, identify, execute, um, and you know, every team would go through that process where really try to understand the, the root cause of the issue and then identify the best opportunity to go solve for that issue or that op that upside. Once you truly understand it and then go execute, but too many people put the, you know, the, the understandings flimsy, or they identify the wrong problem to solve, or they kind of, you know, do the ready fire aim thing where they just dive into it. So I think that, and I think the kind of the loop in hacking growth of like understand analyze data, you know, kind of prioritize experiments. We kind of get at that, but, um, I think that's probably an area that is undervalued in the entire process.
Speaker 2 00:26:40 Right. And, and, um, I'm definitely guilty of pushing people to like, you know, uh, more experiments better. But we, we talked about in the book as well. Like I think we, we looked at the, the, the high tempo often. It's a Baylor at the time. And just like, yeah, you just, you learn more through experimentation. But a lot of times when I'm recommending more experiments is better than less it's that you've got teams that think they're experimenting a lot, but when they actually step back and count their experiments, they're doing a few per year. And if you're not experimenting, you're not learning, but I think it's this combination of increase the velocity of experiments, but do them better. And part of doing them better is to, is to make sure you're experimenting and high leverage opportunities that you really understand what's going on. And then,
Speaker 4 00:27:31 Yeah, and I think like speed creates a set of interesting constraints that then helps you. De-risk a lot of the, kind of the downsides of the big bets that we were just talking about. Right. Like, Hey, if I know I have to get this out, I'm going to scope it down to just the most important thing that I think I need to learn. Right. Like I always ask my team when I get like a big initiative or whatever is like, what's the, what's the, what's the one underlying assumption that must be true for everything else to work. Right. Like, what's that one thing that if that's not true, everything else doesn't matter. And then just go prove that the thing that, that, um, and so, yeah, and then I also think like the high tempo process, like when we, we set up a team here called growth optimization, um, uh, and there, and we set up a cross-functional working group for them called general acceleration where their sole goal was to try to drive the experimentation rate as high as possible to see where our system is broke.
Speaker 4 00:28:31 Right. They're basically trying, like you understand that there's latency in all areas of the business. And then we're just like, go try to run as many experiments as you can and come back and report when things start to fall apart. And that's actually a really helpful learning, uh, when you're kind of in a leadership position, because it really starts to show you where the constraints are in your own system. And so, yeah, I think like I'm a big fan of, of still of like moving as fast as possible. Um, but I say like move fast, like an F1 car and not like a runaway train, you know,
Speaker 3 00:29:01 I was going to ask if that, uh, if that was attract behind you so
Speaker 4 00:29:05 Spa,
Speaker 3 00:29:07 So we'll have lots of talk about it after yesterday. Yesterday's a grand Prix. That was an exciting one, but I digress. Um, uh, I think when you and Sean wrote the book and unless I'm incorrect, you didn't really have much e-commerce experience. Is there anything that, you know, nah, no, no. Now ha coming from the Shopify world that just doesn't hold up, would you write a different book today if, uh, for just specifically for e-commerce or do a lot of things I'm still apply?
Speaker 4 00:29:34 Yeah, I th I think, um, I always think of hacking growth is two books in one there's the first of the first half, which is the method kind of the playbook. I think that part applies generally everywhere, the second half, which is really about the varying stages of the funnel and some specific tactics that you can do. I think those, like when, when we talked to the publisher about writing that second half of the book, Sean and I both told them, like, we'll do it, but you should know that some of these tactics are going to be out of date, the moment, this thing hits, hits print, and yeah. Before, right. Yeah. I'm going to be out of date even when the book lands on shelves. And so four years later, I think that section kind of shows some, some it's a little long in the tooth.
Speaker 4 00:30:17 Um, uh, but yeah, I think specifically you can take that method and generalize that to almost any business model, um, but the specific tactics or areas. Yeah. I think obviously in e-commerce, you're, you're very worried about kind of, um, you know, building that, that audience that we talked about earlier, you kind of want the thousand true fans. Um, you want to engage them in community. You obviously worried about average order value, uh, value and lifetime value of that customer repeat buying rate. And so I think a lot more specific tactics around how to do that are, are, um, I mean the best place to do that is to go like experiment, uh, yourself, but also there's a lot of great brand practitioners, uh, DTC, uh, people online, uh, that you can learn from, um, that are really talking about like the very specific things to do to drive that business model. Yeah. And I don't think our books served any particular, you know, it was written to be a generalizable playbook and not to like specifically solve any one business models, uh, um, needs. Um, I think we probably over index on SAS a bit in it, but, um, but otherwise, yeah, so I think I would, I would write specific sections for different business models, for sure.
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Speaker 2 00:32:31 I find it pretty interesting that, uh, you know, as you said, Facebook is kind of the, the prototype when everyone thinks about growth process, growth team, north star metric, all these, all these concepts around growth. A lot of them were either, uh, born in Facebook or, you know, polished at Facebook and Facebook has a lot of credit, but you've seen all these people graduate from Facebook and, and go into all these other organizations and bring that learning, and then tweak that learning to their unique situation. In fact, we interviewed one of your former colleagues on Friday, uh, she's running growth at Instacart now. Uh, Grina CIA. And, uh, she, you know, it was, it was just so interesting to see, you know, all of the she's, she's relatively new there, like said in the last maybe six months or so, but just, you know, all of the adjustment adjusting and tweaking to the Instacart, uh, situation, um, from, from Facebook, um, you know, I know you and Luke both, uh, came from, from Facebook at, uh, Leva skew at Shopify. Yeah. How, how much of that kind of, oh, you go into it thinking we're going to do it just like we did at Facebook. And then you, you do all of that adjusting. How much of that adjusting have, do you find yourself still adjusting or do you feel like you've got a really good playbook for e-commerce now?
Speaker 4 00:33:57 Yeah, so I think, well, one on, on our team we're really solving a SAS business model, right. It's really because we're solving for the merchant, um, where basically the number of stores that are running online. So we are, it's really a SAS, uh, funnel, you know, it's, uh, try Shopify for free 14 day free trial, pick a plan at the end of it. And then how do we make sure that you set up and sustain success? So we're really focused on the MRR and the number of versions contributing MRR to the business. So that part, um, you know, I think pretty like learned a lot at Qualaroo before that. And, and so, uh, that's kind of where some of that experience comes in, but I definitely think the, um, uh, the, the principles stay the same, right? Like the underlying first principles about growth stay the same regardless of the business model.
Speaker 4 00:34:48 But then you really have to understand, like, it could go into back to this understand, identify, execute piece. You can't just kind of come in and expect that all this stuff that you did over here is going to work over there. You really have to understand the business model, the pain points. Um, you know, one of my favorite parts about Shopify, um, that's a bit counterintuitive is that Shopify has a pretty high, uh, churn rate for standard merchants. Right? And, and we do try to make entrepreneurs successful. We worry about retention and activation, but our goal is not to drive churn as low as possible. Right. And so like, because one of the things that if you try to drive, turn as low as possible is you would self select for the highest quality audiences, right. You would try to find out who are the audiences that are most likely to retain and therefore kind of narrowing the scope of your overall pool of entrepreneurs and people that you can attract.
Speaker 4 00:35:42 And so we basically want to make entrepreneurship accessible to everyone, and we want to make it as easy as possible to try an online store for anyone. And so by doing that, you're going to have to accept a naturally higher churn rate because people that, you know, just it's just a numbers game, it's kind of like Amazon web services allows you to create a web app really inexpensively. So you should expect lots more of them, but many more of them to fail. And so like, if you look at some of our other competitors who try to optimize for like mid-market or small business or whatever, they're kind of going after a narrow segment where Shopify really is a mission led in its desire to be as broad as possible. And so I don't think you can just kind of take tactics and slap them on to business models. You have to understand what you're trying to solve for. Um, but that said the principles of rapid experimentation and hypothesis led great data understanding, um, moving fast, uh, you know, uh, removing friction think desire. Like these things are generally applicable. I think.
Speaker 3 00:36:45 Yeah. I wanted to ask you, um, you've gotten back to this idea that I think you said it was from Facebook, this idea of understand, identify, execute seems to be a recurring theme for you in terms of how to drive success for people who are making a move into it from one business to another. Uh, Sean just published an article about moving from marketing to product. Um, so it's, you know, it's a common theme. People move around. Um, I'm curious if you have advice for people who are just like, if someone's joining your team at Shopify today, how would you get them to not make that mistake of ready, aim, fire, and starting with either executing or identifying really work back from the very beginning? Any, any recommendations there?
Speaker 4 00:37:27 Yeah. I think the thing that I've really come to value are people who are really strong, structured thinkers, right? Like logical reasoning structured thinking is really, I think the hallmark of people who are great at growth, um, particularly at scale, you know, like at Facebook, you essentially have infinite money and infinite resources like being cash constraint is not a constraint that you face as a team being engineering constraint is not a constraint that you face as a team. And so the constraint is in the quality of the ideas. Um, and so really being able to bring strong, structured thinking to an ambiguous space where you can do anything, literally it can build whatever you want. Um, you know, we, we would have brainstorms where we're like, Hey, we should buy a, a wireless operator, right? Like, can we buy T-Mobile? You know? And so like when you're kind of like when the constraint is such, that it's really coming down to the ability to like really get the highest quality ideas around and most clear view of reality, that's, that's the thing.
Speaker 4 00:38:38 So I push all of my teams to work on structured thinking, quality of thinking. There's a great book called the pyramid principle by Barbara Minto, which is about how to like organize, speak, and think and write and structured thinking. Um, there's a great book called how to think, like a rocket scientist, uh, another book called the model thinker, um, uh, Farnam street blog talks a lot about, uh, you know, mental models and structured thinking. And so like people that are really strong on that tend to do really well. People with degrees in math, accounting, um, you know, uh, science like tend to kind of have, have that structured, uh, thinking. And that was something I was not good at. Um, uh, I, I did not get good at that until I got to Facebook. And actually I realized I was getting hammered in meetings cause I w was just getting, you know, out argued basically. And so, um, I actually did the LSAT prep because the L sat is one of the best, uh, evaluations of structure thinking that exists out there. And so I, I prepped, like I was going to take the LSAT and that dramatically ramped my awesome
Speaker 3 00:39:53 We'll help you with arguing on the shirt to train as a lawyer.
Speaker 4 00:39:56 Absolutely. Yeah. It helps with argumentation rhetoric and like actually like solving the thing.
Speaker 3 00:40:01 Yeah. It's interesting how it just, it gives insights into how you approach getting unstuck. And that's sort of the question I want to ask you is have there been any specific challenges, either, maybe a Shopify or Facebook that were really difficult to overcome for you and your team and going back to just sort of the basics of the book, um, helped you get unstuck from there?
Speaker 4 00:40:24 Yeah, it's a good question. I think, um, so at Shopify, I think it really was kind of what we talked about, where it's like, Hey, if we ship something and we're done with it. And, um, as opposed to like ship something, understand the impact, understand what worked, what didn't take another shot on goal, double down. If it's working iterate, if it's not, you know, it was kind of functioning much more as like a traditional marketing team. And, and so like really bringing that, that iterative approach that we advocate in the book was like super helpful to kind of, you know, get people thinking about, okay, this is not a project, but this is a work stream. This is an opportunity that we're going to just like go, we believe in it because we truly understand the opportunity there and we understand what the problem is.
Speaker 4 00:41:13 And so we are committed enough that we're going to go, like, try to figure this out, but it's, it might not be on our first shot, but like, even if our execution is not right the first time, we still believe in our understanding and our identification enough to kind of like keep going after that area. And so I think that's something specifically from the book, uh, that that has really helped. Um, and then I think, you know, kind of, we talked a little bit about big bets and, um, optimizations, I think kind of, you know, understanding that growth changes as you scale, uh, is important because some of the tactics that you would rely on, um, early on, don't give you the sustained growth over time. Right. So if you're small, you know, if, uh, like when we were at, um, you know, Inman, um, you know, running a webinar with a, uh, part, a partner, um, could give you a bunch of signups and that was a great spike.
Speaker 4 00:42:08 And we're like, oh, awesome. You know, it's helping us, you know, build that user base. Um, but then you're like, Hey, you know, can we scale that out? Can we run several webinars? And then you start to hit diminishing returns. Well, like Shopify a scale. If you have a team working on a webinar, cool. They can run a webinar if they get like, you know, a thousand leads from it, it's like a drop in the bucket, right. It actually, doesn't won't materially move it. Even if you could run, you know, our webinar every day and get, you know, a thousand leads every day, it would still for that effort when kind of compute. Right. And so really helping people shift their thinking in terms of okay, for the stage of growth that we're at and where we're at on that trajectory and our scale. How do we think about the opportunity sizing of our different initiatives and prioritize that way and really kind of do that work. Like I think, you know, that opportunity sizing the ice, uh, framework, all of those things like bringing that rigor is, is really critical to helping eliminate the best bets. And, and I think every team, no matter the scale can constantly get better at that.
Speaker 2 00:43:15 So, so another question on that concept of growth and changes as you scale, what, what does the, how do you know, obviously there's not like a one size fits all growth team organization, but how do you think about what the right way to approach setting up a growth team or optimizing a growth team is at different scales? I think probably a lot of what we wrote about was more on the, you know, 10 person, growth teams, sort of size of things you've obviously been on with teams that have much bigger growth teams, but let, let me, let's take like a hundred person growth team. What would, how would you think about optimum building and optimizing a hundred percent growth team?
Speaker 4 00:43:55 I think it goes back to like what you're trying to solve for so real quick at, at Facebook people kind of talk about the Facebook growth team, but there's actually three different flavors of growth teams at Facebook. So you have the growth team led by ho Havi Oliveira, and, um, that is kind of core growth. They're really focused on just, you know, monthly, active users, daily active users, and the inputs that go into those metrics. Right? So, um, uh, login, uh, rate, sign up, rate friending, uh, rate, um, those types of inputs. And so that's really everything else relies on people using Facebook daily. So they're kind of, they own all of those things, whether it's notifications, friend requests, um, being able to log in easily, all of that type of stuff. And so core growth does that. And that's really their focused. Those are their north star metrics.
Speaker 4 00:44:46 Then you have the growth teams on any individual product team like marketplace has its own growth team. And they're really focused on for the number of people that use Facebook. How many people use marketplace, how many people sell stuff on marketplace? How many people buy stuff on marketplace? How many people come back and use it on a weekly basis or whatever. And every product team has a growth team. And then you have a team called product growth, which is like a center of excellence team that they act as like consultants that go out and they embed with those product growth teams to help them find growth opportunities and understand their funnels and then help those product leaders on those growth teams, prioritize experiments, feed those learnings back into the central team that then can be redistributed back out. So you kind of get this network effect of, of learning.
Speaker 4 00:45:36 Um, so I think, you know, at Shopify, our growth teams, a few hundred people, um, right now, and, uh, the way that we're organized is against 10 key priorities that we have for us. Um, and so we, we call them missions, but they're really this cross-functional working model that includes marketers, designers, engineers, data, scientists, operations, people, you know, all in one cross-functional operating mission or pod that is working against a shared roadmap. So we have, you know, a cross functional team for our paid channels. We have a cross-functional team for our organic channels. Uh, we have a cross-functional team for our international markets. We've got one for activation, we've got one for retention. Uh, we've got one for our website platform, uh, new segments, uh, you know, and, and so on. And so basically articulating at the high level strategy, what we think our biggest opportunities for leverage are as a team and then deploying those cross-functional resources into each of those missions accordingly. So some of those missions are more heavy on the channel side. Some are more heavy on the product side, some have more data and some have less data. So it it's we use it. That's kind of how we do it.
Speaker 2 00:46:49 And how flexible is that? Are you, are you shifting those around as new, new high leverage opportunities emerge or is it like a constant optimization where they become such specialists in that more focused area that they stay on that for a long time?
Speaker 4 00:47:04 Yeah. Some it's a bit of both. Some are very enduring, right? Like, um, Google ad words makes up a huge chunk of our paid search budget that will never not be important. Right. We need people who are constantly figuring out how to maximize that channel and share that
Speaker 2 00:47:19 Expertise in that channel. You don't want to pull them off and put them in something
Speaker 4 00:47:22 Else. Yeah, exactly. But for others, some are temporary, right. Like some are more short-lived. Um, and so, um, those can flex around, um, you know, based on like where we're currently working on a product called link pop, which is like a Lincoln bio tool. Right. Um, it's, it's in beta right now. And so there's a specific mission around like getting that product out of the door, out the door, um, and they'll continue to iterate on it and get it to a point where we believe it's like highly performant, but at some point we might move resources around, off of that once that hits like a steady state or pull back because I had to like, you know, keep the lights on, but kind of, um, move some resources to other points. So, yeah, it's a bit of both.
Speaker 3 00:48:06 I'm curious with your, you know, with those different structures that you talked about at Facebook, um, your role now, I think your title is specifically VP of growth, whereas at Facebook and some of your other previous experiences more focused, I think specific the title was more about product management. I'm curious if that's just semantics and you, oh, you know, you're, you're a growth guy. Obviously you wrote the book, um, but it's, is there, well, Sean gets some credit for writing. Is there, is there a significant difference there?
Speaker 4 00:48:36 Yeah, I think so. Um, at, at Facebook I lead a product area. Like I owned a product end to end. I had, I had a growth team in my product team, but I also had a core product team. I had a, um, integrity team. I had a performance reliability engineering team, had a big bet team and I had a machine learning team. And so I really had a full stack, uh, products, uh, team at Shopify. My responsibility really is focused more on customer acquisition purely. So I own like all of our global customer acquisition for our self serve merchants. And so it really is more of that channel focused, um, marketing focused. Uh, so it actually is quite different than the work that I did, uh, at Facebook. Um, and the way that our growth team works at Shopify is I lead kind of the growth marketing functions, which has all the customer acquisition functions. My peer Archie Abram's leads growth product, which is all the activation and retention. And we all report up to Luke, which goes after self-serve collectively. And then we work. Cross-functionally like, all of our teams are embedded with one, with one another into those missions that I've talked about. So that's kind of how we're organized, but yeah, I'm very much more into the channels now than I was at Facebook. Facebook doesn't really have a customer acquisition problem. So, um, you know, it's a much more kind of product, uh, retention focused.
Speaker 2 00:49:59 Yeah. So, so let's, let's kinda, as we get toward the end here, um, you know, I know you're, you're constantly bringing in talented people into Shopify, um, and trying to bring in talented people into your growth team. So I think we, we look at kind of both angles on that. What do you look for? And then at the same time, uh, you know, you've talked about you look for, for structured thinking know to some degree you kind of laid out some attributes, but in terms of, uh, for the individuals that aspire to be on a team like Shopify guys, how should they go about developing the skillset that would make them super attractive to you guys? So if you could kind of take it from both those angles, that would be helpful.
Speaker 4 00:50:41 Yeah, for sure. So I, what I look for is I look for, like you said, really strong structural thinking I wanted, I want people that can solve hard problems. My number one question that I ask is like, tell me about a hard problem that you faced at work, how you solved it and whether you able to solve it or not. It's actually okay if they don't don't solve it. But what I'm actually looking for is like a really gnarly, difficult problem that they kind of were able to reason about break it down, you know, maybe kind of like, like, uh, you know, the Gordian knot kind of concept that no one's able to undo or cut-through, and they're actually able to do it. Um, because I think that that tests for a lot of things, it tests for like resilience, grit, innovation, um, you know, taking multiple shots on goal, breaking down, being good at argumentation, all of that type of thing.
Speaker 4 00:51:31 So that's really important also look for, for creativity, people who kind of think outside the box, so, you know, Hey, how would you grow this thing? Uh, 10 X, uh, but also like for people that are highly technical, um, because I think, uh, you know, being able to, self-serve being able to understand, you know, kind of goes hand in hand with the structure thinking oftentimes. So, um, yeah, so I think the things that I would, uh, recommend for people that are trying to work as like work on all those things, work on structure, thinking work on technical, uh, execution, right? Like you can take a, my SQL class on you to me and get a reasonable handle on how to pass like a SQL loop. Um, pretty, pretty easily, you know, go grow something on your own, start a podcast, start a Shopify store, start a blog, uh, started take talking account, like go figure out how these things grow.
Speaker 4 00:52:26 And like, you know, I think growth is like law or medicine. It's a practice. Um, you know, you need to like constantly, you need to go do it. Uh, you can't learn to hit a baseball by reading a book about it. I don't think you can necessarily learn all you need to know about growth, um, by just reading a book about it, except if it's hacking growth. Um, and, uh, that one proves the rule. Right. Um, and, uh, yeah, so those are the, those are the things that, that I look for, but like, for example, for a large number of rolls onto the Shopify growth team, you have to be able to pass a cul loop. Okay. But you actually can't get the job. It's kind of similar
Speaker 2 00:53:09 To Facebook as well,
Speaker 4 00:53:10 Right? Yeah. Yeah. We kind of said, what are the things that, how do we up the technical capability of our team? Um, when I started at Shopify, we had like 12 engineers and six data scientists over the last year, we've hired 140 engineers, 65 data scientists, um, like a much more
Speaker 2 00:53:29 Technical that's all in the marketing.
Speaker 4 00:53:31 That's all in our growth. That's just, just in our growth team. Yeah.
Speaker 3 00:53:35 Can I ask both of you a question if you're going to write hacking growth tomorrow, what would the, what would the name of the one chapter be that isn't there today? That would be there now.
Speaker 2 00:53:47 I got, I got something in my head. Go ahead. Yeah.
Speaker 4 00:53:49 Yeah. Mine, mine, mine would be understand, identify, execute. Okay. Would be that it would be that,
Speaker 2 00:53:55 Oh, that's better than mine. So yeah, that's what mine would be too. Now my mine would definitely be more along the lines of where I get all the feedback and struggle from, from the book is like I, on an individual level, I love all these concepts, but when I go into my company and try to do these things, I can't, um, the company culture rejects it, the inertia of everything we've done. So I, it would be something about how to, how to get your team to be receptive to a test, learn process and tech to actually adopt that on a, on a team level.
Speaker 4 00:54:29 Yeah. That's a very, that's very real, really real, very real pain point. For sure.
Speaker 3 00:54:33 It's funny because you know, I, while I guess while you guys were actually writing the book, I was sort of starting my tenure at Deltech. And I had the advantage of, you know, having chats with Shawn. Um, and he was giving me his thoughts and advice. And, you know, I think the same things that you, that you were just mentioning, Sean, the struggles about actually implementing it were the same struggles that I actually encountered. Um, but I think what the book does that at least did for me is like, it just kept giving me, like, the one thing I could do is just keep being resilient each time we failed that you keep going back and trying again, try it again. And what the book does is it gives you that starting point and you say, well, I'm struggling with this part of it. Why isn't that working?
Speaker 3 00:55:14 We go back to the book and it's like, well, how are you prioritizing? How are you thinking about this? Um, but I do think, uh, Morgan, to your point that this is something I think I've learned more over the last couple of years too, is really understanding the problem is so, so important. And I think the, the great thing about the hacking growth process is it, you know, it, it really gets you thinking about using experiments to drive improvement, but it's so hard. Like the, you know, I, I wrote a, an article called how to ruin an experiment. Um, and it's like, you know, I just was looking at it a few weeks ago. Like, there's like, I'm like these same mistakes or the same mistakes that I was making five years ago that I still see teams make. I still probably would make them myself and helping guide teams. It's just, it's really hard to get the flywheel going, but having a starting point to say, this is what the flywheel should look like and just keep working it, I think is super valuable. So I appreciate the book. I mean, I'm, I'd still like a shot to replace my signed copy of that. Somebody stole from me, but
Speaker 2 00:56:21 Yeah, you might, you know, it'd really good is if you ever, one of the few people who actually have a copy of that signed by both Morgan and I, and there you go.
Speaker 3 00:56:29 Yeah, it was. And, uh, and the reason it got stolen is the wrong word. The reason that is no longer with me is because I did make it when I was working at Deltek. I basically made a required reading for anyone who joined our team, because I did think it was such a great starting point to get everyone aligned on how to think about how growth is made. So,
Speaker 2 00:56:49 Yeah, and, and, and I think that's one of the ways to overcome that challenge that I talked about of teams not getting on the same page, the number, I'm sure you get this a lot too. Morgan, the number of founders, CEOs, team leaders that, that say it's required reading on my team, um, accelerates every single year. And, and, uh, that's, that's super exciting for me, but I think it's, it's because people are running into that problem that I said, and if you can at least get everyone talking the same language and, and thinking about growth in the same way, they're, they're much more likely to be successful with it.
Speaker 4 00:57:21 Yeah. And I'm actually really excited to see where like web three goes, um, kind of like all these, like, I think there'll be new growth patterns and things that emerged that I'm super excited for, uh, in the next next phase of the web.
Speaker 2 00:57:34 Yeah. So, um, I think it's time to take the dog out for toilet. No, it's good. It's, he's reminding us, we're coming to the end of the hour. You have a little alarm set next to you. That makes it, um, but, uh, but yeah, go ahead, Ethan.
Speaker 3 00:57:52 Yeah. Sean, I think you should take, I think you should ask the final question that we always ask, but before we do that, um, just because you did ask, uh, Morgan about what he looks for in people, I just wanted to give Morgan, I would think that Shopify is just a fantastic company to work for working on your team would be pretty exciting. Um, you've given everyone the playbook for getting a job with you. I mean, you know, grit, innovation, creativity, highly technical learn SQL. Um, but, uh, just while, you know, while our audience is listening, is there, are there any roles that you wanted to point out that you're trying to hide for hire for right now or any, anything, uh, our audience might be interested in? Yeah.
Speaker 4 00:58:25 I'd love to hear from you feel free to email me [email protected]
. We were hiring across the board and growth. Um, international growth is a particular focus right now. Um, lifecycle marketing, email marketing particular focus right now, um, paid acquisition. So whether it's like paid social paid search definitely would love to hear from you. Um, so those are the kinds of the big areas. Uh, but yeah, I mean our team doubled last year, it will probably double again this year. So, um, if you want to learn about Shopify and join the rocket ship com definitely drop me an email.
Speaker 2 00:59:04 Awesome. Well, um, yeah, I'm going to end on the one question, but I feel like we've, uh, we've kind of hit this a lot of times. We always ask our guests this, if, if you have nothing else to add, just say I got nothing else on now, but what do you feel like you understand about growth now that you may not have understood a couple of years ago?
Speaker 4 00:59:23 Yeah, I think the most, the thing that I understand now is just like the level of precision that you can kind of bring to it. I think it goes back to a bunch of the themes you've talked about, but I think, you know, what really impressed what really kind of like blew my mind when I went to Facebook was just the, the level of, you know, I, we can have bureaus, I can tell you stories about the types of problems we solve that were just like, so precise that it was kind of incredible, but I think, yeah, just really upping that logical reasoning and kind of structure thinking bar is the thing that, um, I thought I understood, but learned that I had a lot to learn still.
Speaker 2 01:00:00 Awesome. Awesome. Well, on that note, let's, let's go ahead and wrap it up. Usually I do a, uh, a Roundup of, of everything we've covered, but there's so much my head's kind of exploding, so I'm not going to try to parse any one thing out of it. So, Morgan, thank you so much for coming on the breakout growth podcast. Um, yeah, it's good to finally have you on now that we've worked the kinks out with about 60 other guests before we bring in you on,
Speaker 4 01:00:25 I appreciate it. That was a lot of fun.
Speaker 2 01:00:26 Yeah, definitely. Awesome. And, uh, and for everyone tuning in, thanks for tuning in, thanks has been really a treat for me to have both of your perspectives today.
Speaker 1 01:00:41 Thanks for listening to the breakout growth podcast. Please take a moment to leave us a review on your favorite podcast platform and while you're at it subscribe. So you never miss a show until next week.